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Spatial-Rank Order Selection Filters, Kenneth Barner, Russell Hardie May 2015

Spatial-Rank Order Selection Filters, Kenneth Barner, Russell Hardie

Russell C. Hardie

Chapter 3: "Spatial-Rank Order Selection Filters"
3.1 Introduction
3.2 Selection Filters and Spatial-Rank Ordering
3.3 Spatial-Rank Order Selection Filters
3.4 Optimization
3.5 Applications
3.6 Future Directions


Gradient-Based Edge Detection Using Nonlinear Edge-Enhancing Prefilters, Russell Hardie, Charles Boncelet May 2015

Gradient-Based Edge Detection Using Nonlinear Edge-Enhancing Prefilters, Russell Hardie, Charles Boncelet

Russell C. Hardie

This correspondence examines the use of nonlinear edge enhancers as prefilters for edge detectors. The filters are able to convert smooth edges to step edges and suppress noise simultaneously. Thus, false alarms due to noise are minimized and edge gradient estimates tend to be large and localized. This leads to significantly improved edge maps.


Ranking In Rp And Its Use In Multivariate Image Estimation, Russell Hardie, Gonzalo Arce May 2015

Ranking In Rp And Its Use In Multivariate Image Estimation, Russell Hardie, Gonzalo Arce

Russell C. Hardie

The extension of ranking a set of elements in R to ranking a set of vectors in a p'th dimensional space Rp is considered. In the approach presented here vector ranking reduces to ordering vectors according to a sorted list of vector distances. A statistical analysis of this vector ranking is presented, and these vector ranking concepts are then used to develop ranked-order type estimators for multivariate image fields. A class of vector filters is developed, which are efficient smoothers in additive noise and can be designed to have detail-preserving characteristics. A statistical analysis is developed for the class of …


Lum Filters: A Class Of Rank-Order-Based Filters For Smoothing And Sharpening, Russell Hardie, Charles Boncelet May 2015

Lum Filters: A Class Of Rank-Order-Based Filters For Smoothing And Sharpening, Russell Hardie, Charles Boncelet

Russell C. Hardie

A new class of rank-order-based filters, called lower-upper-middle (LUM) filters, is introduced. The output of these filters is determined by comparing a lower- and an upper-order statistic to the middle sample in the filter window. These filters can be designed for smoothing and sharpening, or outlier rejection. The level of smoothing done by the filter can range from no smoothing to that of the medianfilter. This flexibility allows the LUM filter to be designed to best balance the tradeoffs between noisesmoothing and signal detail preservation. LUM filters for enhancing edge gradients can be designed to be insensitive to low levels …


Infrared Image Registration And High-Resolution Reconstruction Using Multiple Translationally Shifted Aliased Video Frames, Mohammad Alam, John Bognar, Russell Hardie, Brian Yasuda May 2015

Infrared Image Registration And High-Resolution Reconstruction Using Multiple Translationally Shifted Aliased Video Frames, Mohammad Alam, John Bognar, Russell Hardie, Brian Yasuda

Russell C. Hardie

Forward looking infrared (FLIR) detector arrays generally produce spatially undersampled images because the FLIR arrays cannot be made dense enough to yield a sufficiently high spatial sampling frequency. Multi-frame techniques, such as microscanning, are an effective means of reducing aliasing and increasing resolution in images produced by staring imaging systems. These techniques involve interlacing a set of image frames that have been shifted with respect to each other during acquisition. The FLIR system is mounted on a moving platform, such as an aircraft, and the vibrations associated with the platform are used to generate the shifts. Since a fixed number …


Spectral Band Selection And Classifier Design For A Multispectral Imaging Laser Radar, Russell Hardie, Mohan Vaidyanathan, Paul Mcmanamon May 2015

Spectral Band Selection And Classifier Design For A Multispectral Imaging Laser Radar, Russell Hardie, Mohan Vaidyanathan, Paul Mcmanamon

Russell C. Hardie

A statistical spectral band selection procedure and classifiers for an active multispectral laser radar (LADAR) sensor are described. The sensor will operate in the 1 to 5 mm wavelength region. The algorithms proposed are tested using library reflectance spectra for some representative background materials. The material classes considered include both natural (vegetation and soil) and man-made (camouflage cloth and tar-asphalt). The analysis includes noise statistics due to Gaussian receiver noise and target induced speckle variations in the LADAR return signal intensity. The results of this analysis are then directly applied to an artificially generated spatial template of a scene consisting …


Hybrid Order Statistic Filter And Its Application To Image Restoration, Elizabeth Thompson, Russell Hardie, Kenneth Barner May 2015

Hybrid Order Statistic Filter And Its Application To Image Restoration, Elizabeth Thompson, Russell Hardie, Kenneth Barner

Russell C. Hardie

We introduce a new nonlinear filter for signal and image restoration, the hybrid order statistic (HOS) filter. Because it exploits both rank- and spatial-order information, the HOS realizes the advantages of nonlinear filters in edge preservation and reduction of impulsive noise components while retaining the ability of the linear filter to suppress Gaussian noise. We show that the HOS filter exhibits improved performance over both the linear Wiener and the nonlinear L filters in reducing mean-squared error in the presence of contaminated Gaussian noise. In many cases it also performs favorably compared with the Ll and rank-conditioned rank selection filters.


Application Of Multi-Frame High-Resolution Image Reconstruction To Digital Microscopy, Frank Baxley, Russell Hardie May 2015

Application Of Multi-Frame High-Resolution Image Reconstruction To Digital Microscopy, Frank Baxley, Russell Hardie

Russell C. Hardie

A high-resolution image reconstruction algorithm previously used to improve undersampled infrared airborne imagery was applied to two different sets of digital microscopy images. One set is that of medical pap smear images, and the second set contains metallurgical micrographs. Both the pap smear images and the metallurgical micrographs are undersampled, thus causing loss of detail and aliasing artifacts. The algorithm minimizes the effects of aliasing and restores detail unobtainable through simple interpolation techniques. Both applications demonstrate improvement by use of the image reconstruction algorithm.


Robust Phase-Unwrapping Algorithm Using A Spatial Binary-Tree Image Decomposition, Russell Hardie, Md. Younus, James Blackshire May 2015

Robust Phase-Unwrapping Algorithm Using A Spatial Binary-Tree Image Decomposition, Russell Hardie, Md. Younus, James Blackshire

Russell C. Hardie

The search for fast and robust phase-unwrapping algorithms remains an important problem in the development of real-time interferometric systems. Our phase-unwrapping approach uses a spatial binary-tree image decomposition to permit maximum parallelism in implementation. At each node in the tree structure, a single unwrapping decision is made between two image blocks. The unwrapping rule is derived from a statistical-estimation framework. Specifically, a maximum-likelihood estimate of the demodulation term is used. This term can be viewed as that which minimizes a discontinuity-penalizing cost function. We show that the algorithm exhibits a high level of robustness. Quantitative measures of performance are provided, …


Scene-Based Nonuniformity Correction With Video Sequences And Registration, Russell Hardie, Majeed Hayat, Ernest Armstrong, Brian Yasuda May 2015

Scene-Based Nonuniformity Correction With Video Sequences And Registration, Russell Hardie, Majeed Hayat, Ernest Armstrong, Brian Yasuda

Russell C. Hardie

We describe a new, to our knowledge, scene-based nonuniformity correction algorithm for array detectors. The algorithm relies on the ability to register a sequence of observed frames in the presence of the fixed-pattern noise caused by pixel-to-pixel nonuniformity. In low-to-moderate levels of nonuniformity, sufficiently accurate registration may be possible with standard scene-based registration techniques. If the registration is accurate, and motion exists between the frames, then groups of independent detectors can be identified that observe the same irradiance ~or true scene value!. These detector outputs are averaged to generate estimates of the true scene values. With these scene estimates, and …


A Post-Processing Technique For Extending Depth Of Focus In Conventional Optical Microscopy, Taufiq Widjanarko, Russell Hardie May 2015

A Post-Processing Technique For Extending Depth Of Focus In Conventional Optical Microscopy, Taufiq Widjanarko, Russell Hardie

Russell C. Hardie

In this paper, we propose a post-processing technique to obtain optical microscope images with extended depth of focus using a conventional microscope. With the proposed technique, we collect a sequence of images focused at different depths. We then combine the in-focus regions of each acquired frame to compose a single all-in-focus image. That is, a new image with extended depth of focus is obtained. The key to such an algorithm is in selecting the “in-focus” regions from each frame. In this paper, we describe the technique used to identify the in-focus region on every depth slice. Quantitative simulation results are …


Application Of The Stochastic Mixing Model To Hyperspectral Resolution Enhancement, Michael Eismann, Russell Hardie May 2015

Application Of The Stochastic Mixing Model To Hyperspectral Resolution Enhancement, Michael Eismann, Russell Hardie

Russell C. Hardie

A maximum a posteriori (MAP) estimation method is described for enhancing the spatial resolution of a hyperspectral image using a higher resolution coincident panchromatic image. The approach makes use of a stochastic mixing model (SMM) of the underlying spectral scene content to develop a cost function that simultaneously optimizes the estimated hyperspectral scene relative to the observed hyperspectral and panchromatic imagery, as well as the local statistics of the spectral mixing model. The incorporation of the stochastic mixing model is found to be the key ingredient for reconstructing subpixel spectral information in that it provides the necessary constraints that lead …


Performance Analysis Of A New Computer Aided Detection System For Identifying Lung Nodules On Chest Radiographs, Russell Hardie, Steven Rogers, Terry Wilson, Adam Rogers May 2015

Performance Analysis Of A New Computer Aided Detection System For Identifying Lung Nodules On Chest Radiographs, Russell Hardie, Steven Rogers, Terry Wilson, Adam Rogers

Russell C. Hardie

A new computer aided detection (CAD) system is presented for the detection of pulmonary nodules on chest radiographs. Here, we present the details of the proposed algorithm and provide a performance analysis using a publicly available database to serve as a benchmark for future research efforts. All aspects of algorithm training were done using an independent dataset containing 167 chest radiographs with a total of 181 lung nodules. The publicly available test set was created by the Standard Digital Image Database Project Team of the Scientific Committee of the Japanese Society of Radiological Technology (JRST). The JRST dataset used here …


Stochastic Spectral Unmixing With Enhanced Endmember Class Separation, Michael Eismann, Russell Hardie May 2015

Stochastic Spectral Unmixing With Enhanced Endmember Class Separation, Michael Eismann, Russell Hardie

Russell C. Hardie

Improvements to an algorithm for performing spectral unmixing of hyperspectral imagery based on the stochastic mixing model (SMM) are presented. The SMM provides a method for characterizing both subpixel mixing of the pure image constituents, or endmembers, and statistical variation in the endmember spectra that is due, for example, to sensor noise and natural variability of the pure constituents. Modifications of the iterative, expectation maximization approach to deriving the SMM parameter estimates are proposed, and their effects on unmixing performance are characterized. These modifications specifically concern algorithm initialization, random class assignment, and mixture constraints. The results show that the enhanced …


An Algebraic Algorithm For Nonuniformity Correction In Focal-Plane Arrays, Bradley Ratliff, Majeed Hayat, Russell Hardie May 2015

An Algebraic Algorithm For Nonuniformity Correction In Focal-Plane Arrays, Bradley Ratliff, Majeed Hayat, Russell Hardie

Russell C. Hardie

A scene-based algorithm is developed to compensate for bias nonuniformity in focal-plane arrays. Nonuniformity can be extremely problematic, especially for mid- to far-infrared imaging systems. The technique is based on use of estimates of interframe subpixel shifts in an image sequence, in conjunction with a linear-interpolation model for the motion, to extract information on the bias nonuniformity algebraically. The performance of the proposed algorithm is analyzed by using real infrared and simulated data. One advantage of this technique is its simplicity; it requires relatively few frames to generate an effective correction matrix, thereby permitting the execution of frequent on-the-fly nonuniformity …


Subspace Partition Weighted Sum Filters For Image Restoration, Yong Lin, Russell Hardie, Kenneth Barner May 2015

Subspace Partition Weighted Sum Filters For Image Restoration, Yong Lin, Russell Hardie, Kenneth Barner

Russell C. Hardie

The previously proposed partition-based weighted sum (PWS) filters combine vector quantization (VQ) and linear finite impulse response (FIR) Wiener filtering concepts. By partitioning the observation space and applying a tuned Wiener filter to each partition, the PWS is spatially adaptive and has been shown to perform well in noise reduction applications. In this letter, we propose the subspace PWS (SPWS) filter and evaluate the efficacy of the SPWS filter in image deconvolution and noise reduction applications. In the SPWS filter, we project the observation vectors into a subspace using principal component analysis (PCA), or other methods, prior to partitioning. This …


Hyperspectral Resolution Enhancement Using High-Resolution Multispectral Imagery With Arbitrary Response Functions, Michael Eismann, Russell Hardie May 2015

Hyperspectral Resolution Enhancement Using High-Resolution Multispectral Imagery With Arbitrary Response Functions, Michael Eismann, Russell Hardie

Russell C. Hardie

A maximum a posteriori (MAP) estimation method for improving the spatial resolution of a hyperspectral image using a higher resolution auxiliary image is extended to address several practical remote sensing situations. These include cases where: 1) the spectral response of the auxiliary image is unknown and does not match that of the hyperspectral image; 2) the auxiliary image is multispectral; and 3) the spatial point spread function for the hyperspectral sensor is arbitrary and extends beyond the span of the detector elements. The research presented follows a previously reported MAP approach that makes use of a stochastic mixing model (SMM) …


Improved Optimization Of Soft Partition Weighted Sum Filters And Their Application To Image Restoration, Yong Lin, Russell Hardie, Qin Sheng, Kenneth Barner May 2015

Improved Optimization Of Soft Partition Weighted Sum Filters And Their Application To Image Restoration, Yong Lin, Russell Hardie, Qin Sheng, Kenneth Barner

Russell C. Hardie

Soft-partition-weighted-sum (Soft-PWS) filters are a class of spatially adaptive moving-window filters for signal and image restoration. Their performance is shown to be promising. However, optimization of the Soft-PWS filters has received only limited attention. Earlier work focused on a stochastic-gradient method that is computationally prohibitive in many applications. We describe a novel radial basis function interpretation of the Soft-PWS filters and present an efficient optimization procedure. We apply the filters to the problem of noise reduction. The experimental results show that the Soft-PWS filter outperforms the standard partition-weighted-sum filter and the Wiener filter.


A New Computationally Efficient Cad System For Nodule Detection In Ct Imagery, Temesguen Messay, Russell Hardie, Steven Rogers May 2015

A New Computationally Efficient Cad System For Nodule Detection In Ct Imagery, Temesguen Messay, Russell Hardie, Steven Rogers

Russell C. Hardie

Early detection of lung nodules is extremely important for the diagnosis and clinical management of lung cancer. In this paper, a novel computer aided detection (CAD) system for the detection of pulmonary nodules in thoracic computed tomography (CT) imagery is presented. The paper describes the architecture of the CAD system and assesses its performance on a publicly available database to serve as a benchmark for future research efforts. Training and tuning of all modules in our CAD system is done using a separate and independent dataset provided courtesy of the University of Texas Medical Branch (UTMB). The publicly available testing …


A Computationally Efficient Super-Resolution Algorithm For Video Processing Using Partition Filters, Balaji Narayanan, Russell Hardie, Kenneth Barner, Min Shao May 2015

A Computationally Efficient Super-Resolution Algorithm For Video Processing Using Partition Filters, Balaji Narayanan, Russell Hardie, Kenneth Barner, Min Shao

Russell C. Hardie

We propose a computationally efficient super-resolution (SR) algorithm to produce high-resolution videofrom low-resolution (LR) video using partition-based weighted sum (PWS) filters. First, subpixel motion parameters are estimated from the LR video frames. These are used to position the observed LR pixels into a high-resolution (HR) grid. Finally, PWS filters are employed to simultaneously perform nonuniform interpolation (to fully populate the HR grid) and perform deconvolution of the system point spread function. The PWS filters operate with a moving window. At each window location, the output is formedusing a weighted sum of the present pixels within the window. The weights are …


A Collaborative Adaptive Wiener Filter For Multi-Frame Super-Resolution, Khaled Mohamed, Russell Hardie May 2015

A Collaborative Adaptive Wiener Filter For Multi-Frame Super-Resolution, Khaled Mohamed, Russell Hardie

Russell C. Hardie

Factors that can limit the effective resolution of an imaging system may include aliasing from under-sampling, blur from the optics and external factors, and sensor noise. Image restoration and super-resolution (SR) techniques can be used to improve image resolution. One SR method, developed recently, is the adaptive Wiener filter (AWF) SR algorithm. This is a multi-frame SR method that combines registered temporal frames through a joint nonuniform interpolation and restoration process to provide a high-resolution image estimate. Variations of this method have been demonstrated to be effective for multi-frame SR, as well demosaicing RGB and polarimetric imagery. While the AWF …


Computationally Efficient Video Restoration For Nyquist Sampled Imaging Sensors Combining An Affine-Motion-Based Temporal Kalman Filter And Adaptive Wiener Filter, Michael Rucci, Russell Hardie, Kenneth Barnard May 2015

Computationally Efficient Video Restoration For Nyquist Sampled Imaging Sensors Combining An Affine-Motion-Based Temporal Kalman Filter And Adaptive Wiener Filter, Michael Rucci, Russell Hardie, Kenneth Barnard

Russell C. Hardie

In this paper, we present a computationally efficient video restoration algorithm to address both blur and noise for a Nyquist sampled imaging system. The proposed method utilizes a temporal Kalman filter followed by a correlation-model based spatial adaptive Wiener filter (AWF). The Kalman filter employs an affine background motion model and novel process-noise variance estimate. We also propose and demonstrate a new multidelay temporal Kalman filter designed to more robustly treat local motion. The AWF is a spatial operation that performs deconvolution and adapts to the spatially varying residual noise left in the Kalman filter stage. In image areas where …


High-Resolution Image Reconstruction From Digital Video By Exploitation Of Nonglobal Motion, Timothy Tuinstra, Russell Hardie Mar 2015

High-Resolution Image Reconstruction From Digital Video By Exploitation Of Nonglobal Motion, Timothy Tuinstra, Russell Hardie

Russell C. Hardie

Many imaging systems utilize detector arrays that do not sample the scene according to the Nyquist criterion. As a result, the higher spatial frequencies admitted by the optics are aliased. This creates undesirable artifacts in the imagery. Furthermore, the blurring effects of the optics and the finite detector size also degrade the image quality. Several approaches for increasing the sampling rate of imaging systems have been suggested in the literature. We propose an algorithm for resolution enhancement that exploits object motion in digital video sequences. Unlike previously defined techniques, we use an automated segmentation method to isolate rigid moving objects. …